Directory Data & AnalyticsDatabase PlatformsScyllaDB

ScyllaDB

Open Source

About ScyllaDB

ScyllaDB is a high-throughput, low-latency NoSQL database platform designed to handle data-intensive applications requiring predictable single-digit millisecond latencies. It is purpose-built for enterprises managing massive real-time AI workloads, including billion-scale vector search and feature stores. ScyllaDB offers a close-to-the-metal architecture that supports millions of operations per second, enabling organizations to scale fearlessly while maintaining consistent performance.

The platform is suitable for large enterprises needing to process and analyze vast amounts of data in real time, such as e-commerce, AI, and analytics-driven companies. ScyllaDB provides both a fully managed cloud service on AWS and GCP and an enterprise edition with premium features and dedicated support. Its compatibility with APIs like DynamoDB and Cassandra allows seamless migration and integration, reducing operational complexity and cost. ScyllaDB’s open source core combined with enterprise-grade tools and cloud offerings delivers flexibility, scalability, and cost efficiency for demanding AI and data applications.

How to evaluate Database Platforms

This is how the CIOPages Research Team evaluates this category. It is not an assessment of ScyllaDB. It comes from our Enterprise Database Platforms buyer guide.

25%

Data Model & Query Fit

Match of the engine to the workload: relational integrity and joins, document/JSON flexibility, key-value latency; transaction isolation levels and ACID guarantees; SQL standard coverage and dialect quirks; secondary indexes, full-text and vector (pgvector / Atlas Search) support; foreign keys and referential integrity where you need them

20%

Consistency, Scale & HA

Single-primary vs. multi-writer; synchronous vs. async replication and resulting RPO; read-replica and sharding story; horizontal write scale and global/multi-region behavior (strong vs. eventual consistency); failover time, achievable RTO, and how partitions are handled under load

20%

Operability & Managed-Service Experience

Quality of the managed offering (RDS/Aurora, Azure SQL, Cloud SQL/AlloyDB) vs. self-managed burden; in-place and major-version upgrade path; backup/PITR, observability, and connection pooling; autoscaling and serverless options; day-2 toil — vacuum/compaction, index bloat, rebalancing — and the depth of the DBA skills it demands

15%

Licensing & Portability

License class and its real constraints: OSI open source (PostgreSQL, MySQL, Valkey, Redis 8 AGPL) vs. source-available (MongoDB SSPL, CockroachDB enterprise/BSL) vs. proprietary (Oracle, SQL Server); cloud lock-in of proprietary engines (Aurora, Spanner, DynamoDB); wire-protocol and SQL-dialect compatibility that preserves an exit; audit exposure on proprietary metrics

12%

Security & Compliance

Encryption at rest and in transit, TLS enforcement, and key management (BYOK/HSM); row- and column-level security and fine-grained RBAC; field-level / queryable encryption for sensitive data; audit logging; data-residency controls and certifications (SOC 2, ISO 27001, HIPAA, PCI, FedRAMP) on the managed service

Ecosystem & Talent

Driver and ORM maturity across your languages; migration and CDC tooling (logical replication, Debezium, DMS); breadth of extensions and integrations; size and hireability of the talent pool; quality of docs and the support path — first-party vendor vs. third-party (EDB, Percona, Crunchy) for open engines

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